Apache Cassandra is an open-source distributed NoSQL database management system built to handle large chunks of data over various data centers. Cassandra was developed at Facebook to overcome its “inbox search” issue and make it easier to find the conversations. Facebook later open-sourced Cassandra, and it became an Apache Foundation project. Cassandra is a highly scalable database and is freely available under the Apache License 2.0.
Cassandra Basics and Monitoring
Cassandra is a NoSQL database built to provide better scalability and reliability. Cassandra runs on a Java Virtual Machine, and its metrics can be collected using Java Management Extensions (JMX). Databases- were built to serve various applications and need to be high performing and reliable. When a database is low-performing and unable to send and receive a request, you may experience hurdles in the working of various applications. That is why monitoring the database is such a prominent aspect of the healthy performance of a cluster. Monitoring helps in providing a vigorous environment for any database management.
Here we will discuss the effective monitoring of Cassandra with few best practices which are going to help you with Cassandra database throughput performance.
- Physical Resources
Monitoring the physical resources is very critical for smooth database operations. CPU utilization metrics play a pivotal role in Cassandra’s monitoring. If the resources going into the cluster aren’t enough, the database will not perform efficiently. A cluster’s availability highly depends on the node status. Nodes should be in uptime since any lost performance during a node downtime cannot be retained back.
If any node is down, it should be immediately altered. If delayed, it could bring pressure on the other nodes. This alert also helps in knowing the need to repair the node. Every node that is out of the cluster for the default time of more than Three hours needs to be repaired.
- Client Request Metrics
Just like physical requests, client’s requests that are sent need to be monitored as well. Client request metrics provide information related to the communication between the client and coordinator node.
To manage these metrics we need to monitor the number of requests per second. Any cluster can efficiently handle a certain amount of requests per second, but if the request exceeds the number it results in inconsistency.
- Throughput metrics to check on system workload
Checking on throughput Metrics is one of the prominent aspects of Cassandra monitoring. It requires monitoring read and write requests and will help you with keeping tabs on requests nodes are coordinating every second.
Monitoring cache hit rate values also helps with throughput issues. The overloading which causes throughput can be reduced; by adding more nodes.
- Latency to maintain low request times
Tracking of the read and write latency by client applications is the most crucial metric of the Cassandra database. The latency monitoring tracks the speed of the read and writes requests. The main factor affecting latency is the load served by a cluster.
These metrics need to be tracked both separately and as overall values. One needs to be sure that the latency number remains low. A rise in latency number indicates the low capacity to fulfill client requests.
- Garbage collector metrics
The efficiency of Cassandra is highly dependent on the use of GC and, the GC behavior depends on the garbage collector used. Every time the java garbage collection increases, java heap memory gets resized.
Any changes in the parameters affecting the garbage collector need to be monitored thoroughly. Also setting an alert on GC pause will help with the performance of the database.
- Checking on Thread pool Metrics
Thread pool metrics provide information about the blocked tasks. It is a prominent metric when you want your Cassandra queue to keep moving. To ensure the movement: these metrics should be low or at zero.
Monitoring these pools helps in understanding the internal behavior and allows knowing about the pools under pressure due to any blocked or pending task.
Cassandra monitoring is as important as its implementation since it provides an insight into the system of the database and helps in improving overall performance.
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